A method for evaluating the learning concentration in head-mounted virtual reality interaction

Lin, Yi Chun; Lan, Yangfan; Wang, Shunbo

doi:10.1007/s10055-022-00689-5

Cited by 9 publications

(8 citation statements)

References 58 publications

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“…For example, Lin et al fused three dimensions by incorporating facial expressions, visual focus rate, and task mastery as evaluation indicators. The proposed model improved learning concentration and assessment scores by 18% and 15.39%, respectively [17]. However, in this study, each dimension was represented using only one type of data.…”

Section: Concentration Recognition Based On Emotion Behavior and Cogn...mentioning

confidence: 87%

“…Moreover, it fails to consider effectively integrating the three dimensions of cognition, emotion, and behavior. Therefore, there is an urgent need to explore multi-dimensional integration methods for concentration recognition [17].…”

Section: Introductionmentioning

confidence: 99%

“…For example, due to facial occlusion, facial data cannot be easily captured through cameras. Additionally, the commonly used mouse data in online learning environments are not applicable in VR environments [17]. Although Lin et al [17] explored an evaluation method for learning concentration in a VR environment by integrating the three dimensions of cognition, emotion, and behavior, the data extracted under each dimension was single type.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, the commonly used mouse data in online learning environments are not applicable in VR environments [17]. Although Lin et al [17] explored an evaluation method for learning concentration in a VR environment by integrating the three dimensions of cognition, emotion, and behavior, the data extracted under each dimension was single type. Hence, it is urgent to explore the recognition of learning concentration in VR environments by integrating multi-dimensional and multitype feature data.…”

Section: Introductionmentioning

confidence: 99%

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Research on Learning Concentration Recognition with Multi-Modal Features in Virtual Reality Environments

Zhong

et al. 2023

Sustainability

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Learning concentration, as a crucial factor influencing learning outcomes, provides the basis for learners’ self-regulation and teachers’ instructional adjustments and intervention decisions. However, the current research on learning concentration recognition lacks the integration of cognitive, emotional, and behavioral features, and the integration of interaction and vision data for recognition requires further exploration. The way data are collected in a head-mounted display differs from that in a traditional classroom or online learning. Therefore, it is vital to explore a recognition method for learning concentration based on multi-modal features in VR environments. This study proposes a multi-modal feature integration-based learning concentration recognition method in VR environments. It combines interaction and vision data, including measurements of interactive tests, text, clickstream, pupil facial expressions, and eye gaze data, to measure learners’ concentration in VR environments in terms of cognitive, emotional, and behavioral representation. The experimental results demonstrate that the proposed method, which integrates interaction and vision data to comprehensively represent the cognitive, emotional, and behavioral dimensions of learning concentration, outperforms single-dimensional and single-type recognition results in terms of accuracy. Additionally, it was found that learners with higher concentration levels achieve better learning outcomes, and learners’ perceived sense of immersion is an important factor influencing their concentration.

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Section: Concentration Recognition Based On Emotion Behavior and Cogn...mentioning

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Research on Learning Concentration Recognition with Multi-Modal Features in Virtual Reality Environments

Zhong

et al. 2023

Sustainability

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“…Over 40 years ago, visual environments have developed from the original online games (Duncan et al, 2012). (Lin, 2020), predicts that the number of monthly users of VR from 2018 to 2022 will be increased by 75.7%. According to (Petrock, 2020), the number of Virtual World users reached 90.9 million, and specifically, 57.4 million is dominated by US users.…”

Section: Introductionmentioning

confidence: 99%

Teachers’ Perspective Of The Use Of Three-Dimensional Virtual World (3DVW) In Teaching Pronunciation: A Qualitative Case Study

Amaliyah

Arifani

Wongsrikaew³

et al. 2023

UMGESHIC

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The aim of this article is to scrutinize EFL teachers' perspectives on using 3D Virtual World for teaching English pronunciation. The article is a case study with open-ended, in-depth interviews conducted with two Thai EFL teachers. The study finds topics based on a typological analysis of interview data: the use of 3DVW as a learning medium for teaching pronunciation, and teachers' perspectives on teaching using 3DVW. The findings revealed that teachers have a positive perspective on 3DVW as a medium for teaching pronunciation. It has advantages that can help students with their pronunciation understanding. Additionally, teachers serve as role models and facilitators for students during the learning process.

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Research and application of digital electrical substation virtual engineering education system

Li,

Ma,

Zhang

et al. 2024

Comp Applic In Engineering

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The education and training of electrical substations play an essential role for college students and engineers majoring in electrical engineering. However, to ensure the substation's safety production and equipment operation, it is difficult for personnel from external units to enter the site for learning. To overcome these limitations, this paper proposes a virtual interactive training technology method to author an interactive virtual maintenance education system (VMES) for electrical substations. The system aims to build a visual training and education platform for virtual substations to help learners master the station's equipment, operation, maintenance, evaluation, and other processes. Firstly, the system establishes a component‐level virtual interaction element to encapsulate an electrical substation virtual maintenance model that dynamically responds to user operations. The equipment structure and system environment are visually modeled using engineering modeling software. Secondly, a virtual interactive training system is created with the functions of 3D disassembly training, fault tree reliability evaluation, and AHP‐FCE maintenance assessment. Finally, through four operating systems, we evaluate the compatibility of the VMES, and we recruit learners to evaluate and discuss emerging and common educational models. The practical application results prove that the system can significantly improve students' learning efficiency and interest. Meanwhile, due to the increased number of interactive operations in VMES, participants can proficiently master the composition and working principles of equipment in substations, and cognitive load can be reduced.

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A method for evaluating the learning concentration in head-mounted virtual reality interaction

Cited by 9 publications

References 58 publications

Research on Learning Concentration Recognition with Multi-Modal Features in Virtual Reality Environments

Research on Learning Concentration Recognition with Multi-Modal Features in Virtual Reality Environments

Teachers’ Perspective Of The Use Of Three-Dimensional Virtual World (3DVW) In Teaching Pronunciation: A Qualitative Case Study

Research and application of digital electrical substation virtual engineering education system

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